Covers the clinical relevance of big data in otolaryngology, lessons and limitations of large administrative datasets, biologic big data, and much more
Discusses artificial intelligence (AI) in otolaryngology and its clinical application
Presents a patient perspective on big data in otolaryngology and its use in clinical care, as well as a glimpse into the future of big data
Compiles the knowledge and expertise of leading experts in the field who have assembled the most up-to-date recommendations for managing big data in otolaryngology
Consolidates today's available information on this timely topic into a single, convenient resource
1. Big data - Science fiction or clinically relevant 2. Large administrative datasets: Lessons and limitations 3. Sources of high-dimensional data - The electronic health record, health systems, and insurance and payor data 4. Best practices when interpreting big data studies: Considerations and red flags 5. Current big data approaches to clinical questions in otolaryngology 6. Bias in big data: Historically underrepresented groups and implications 7. Artificial intelligence in otolaryngology 8. The patient perspective on big data and its use in clinical care
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